基于模糊搜索理论的组合算法在城市道路交通预测中的应用

Y. V. Leshchik, D. Sonkin, M. Sonkin, S. Khrul
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引用次数: 4

摘要

本文分析了城市道路交通进度预测问题。所提出的数学模型和算法允许使用来自车辆监控系统的交通参数统计数据来解决交通堵塞预测问题。研究了基于已知方法的关系数据库模糊搜索混合准则道路交通状况预测算法。该预测算法已通过一年多的卫星车辆监测数据成功测试。应用所描述的方法可以在交通堵塞预测中取得较高的效果。将所提出的预测结果与常用的平均速度外推法和研究时段的实际数据进行了比较。
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Applying of combined algorithm for prediction urban road traffic based on fuzzy search theory
The article analyzes the problem of road traffic progress prediction in the city. Proposed mathematical models and algorithms allow to solve the problem of traffic jam prediction using statistics about the traffic parameters incoming from vehicle monitoring systems. The algorithm of road traffic situation prediction based on known approaches fuzzy search in relational databases using a mixed criterion. The prediction algorithm had been successfully tested using satellite vehicle monitoring data pick up for more than a year. Application of described methods makes possible to achieve high results in predicting of traffic jam. The results of using the proposed prediction method was compared with widely used average speed extrapolation method and actual data for the study period of time.
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